Dr. Chengbin Wang is an associate professor of School of Earth Resources at the China University of Geosciences (Wuhan). He received his PhD degree of Mineral Prospecting and Exploration from China University of Geosciences in Dec. 2017.   

His research focues on Integration and Interoperability of Non-structured Geological Big Data, GIS-based Mineral Predication via Machine Learning, Construction and Application of Mineral Deposits Knowledge Graph, and LLM and Agent in the Geoscience.

Professional Appointment

07/2018-    Associate Professor, China University of Geosciences (Wuhan)

Recent Honors, Awards & Scholarship

10/2023 Ministry of Natural Resources High-level Science and Technology Innovation Talent Project

10/2017  Best paper award, Conference on Annual Meeting of Geological Society of China

09/2017  C&G Research Scholarship, International Association of Mathematical Geosciences

05/2017  USGS Travel Grants

Funded Project

PI

10/2024-10/2027, Program Research on deep earth big data analysis model

06/2024/05/2026, Construction of knowledge graph of Geology and mineral deposit and AIGC intelligent geoscience information service in Ningxia

04/2024-04/2026 Accurate and intelligent prediction and evaluation of Hunan gold mines driven by geological big data

09/2017~09/2017 IAMG, Text Information Extraction and Knowledge Graph Construction from Geoscience Literature, $ 2,500.

12/2012~06/2014, Chinese Academy of Geological Sciences, Application of Hilbert-Huang and Independent Component Analysis on the Extraction of Metallogenic Information, ¥50,000.

Project Participant

06/2017-   National Key Research and Development Program, 3D geophysical modeling and Mineral Prediction in the deep of Earth Crust, ¥ 4,820,000.

01/2015-   Ministry of Land and Resources, Automatic Indexing and Summarization Research of Geological Report, ¥ 350,000.

03/2013~05/2014 Industry Project, Gold Mineralization and Mineral Predication in the Dahaoshan-Lishan Area, Jiangxi Province, ¥ 400,000.

01/2013~12/2015 China Geological Survey, Geophysical Exploration and Remote Sensing in the Concealed Areas, ¥ 2,500,000.

Publication (*Corresponding author)

（33）张立东，朱亿，张立中，王成彬*.2026.基于随机森林和SHAP可解释性分析的多宝山外围斑岩型铜矿预测与评价.地质科技通报(接收)

（32）Zeng J., Hong Y., Wang C.*, Chen J., and Liu J. 2026. Co-simulation of Continuous and Categorical Variables: Application in the Shuiyindong gold deposit modeling. Froniter in Earth Science. (Accepted)

（31）Zhu J., Wang Y., Tong W., Li S., Wang M., and Wang C.* 2026. Gold Deposit Ontology Guides Large Language Model to Transform Text into Knowledge Graphs for Gold Deposits. Minerals. 16(1), 50. https://doi.org/10.3390/min16010050  注：本科生第一作者

（30）Wang M., Wang C.*, Chen J., Wang B., Wang W., Ma X., Ren J., Li Z., Ye Y., Zhang J., and Wang Y., 2025. A Lightweight Knowledge Graph-Driven Question Answering System for Field-based Mineral Resource Survey. Applied Computing and Geosciences. 27, 100268. 

（29）Wu R., Huang M., Ma H., Huang J., Li Z., Mei H., Wang C.*, 2025.A Multi-Temporal Knowledge Graph Framework for Landslide Monitoring and Hazard Assessment. GeoHazards. 6(3), 39 https://doi.org/10.3390/geohazards6030039

（28）吴润泽, 李浩, 梅红波, 王成彬, 朱敏毅, 王红群, 张亮, 胡光鸿, 马明杰, 望致文, 张隆隆, 黄旻, 李振华, 2025. 基于知识图谱检索增强生成的滑坡监测预警系统. 地球科学. doi: 10.3799/dqkx.2025.127

（27）Fu Y., Wang M., Wang C.*, Dong S., Chen J., Wang J., Yu H., Huang J., Chang L., and Wang B., 2025.GeoMinLM: A Large Language Model in Geology and Mineral Survey in Yunnan Province. Ore Geology Reviews, 182, 106638

（26）王成彬*，王明果，王博，陈建国，马小刚，蒋恕，2024. 融合知识图谱的矿产资源定量预测.地学前缘. 31(04):26-36 https://doi.org/10.13745/j.esf.sf.2024.5.3

（25）Wang C.*, Tan L., Li Y., Wang M., Ma X., and Chen J., 2024. Ontology-driven Relational Data Mapping for Constructing a Knowledge Graph of Porphyry Copper Deposits. Earth Science Informatics. 17(3):2649-2660 https://doi.org/10.1007/s12145-024-01307-5.

（24）Wang C.*, Li Y., Chen J. and Ma X., 2023. Named Entity Annotation Schema for Geological Literature Mining in the Domain of Porphyry Copper Deposits. Ore Geology Reviews. 152:105243. https://doi.org/10.1016/j.oregeorev.2022.105243

（23）Wang C.*, Li Y., Chen J. 2023.Text Mining and Knowledge Graph Construction from Geoscience Literature Legacy: A Review. In: Ma X, Mookerjee M, Hsu L, Hills D (eds) Recent Advancement in Geoinformatics and Data Science, GSA Special Paper. https://doi.org/10.1130/2022.2558(02)

（22）Wang C.*, Zhao K-D.*, Chen J. and Ma X., 2022. Examining Fingerprint Trace Elements in Cassiterite: Implications for Primary Tin Deposit Exploration. Ore Geology Reviews. 149. 105082. https://doi.org/10.1016/j.oregeorev.2022.105082

（21）Ma C., Morrision S., Muscente D., Wang C., and Ma X., 2022. Incorporate temporal topology in a deep-time knowledge base to facilitate data-driven discovery in geoscience. Geoscience Data Journal. https://doi.org/10.1002/gdj3.171

（20）Yang X., Chen J., Wang C., and Chen Z., 2022. Residual Dense Autoencoder Network for Nonlinear Hyperspectral Unmixing.  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. https://ieeexplore.ieee.org/document/9815532

（19）Wang C.*, Chen J.*, and Ouyang Y., 2022. Determination of Predictive Variables in Mineral Prospectivity Mapping Using Supervised and Unsupervised Methods. Natural Resources Research. 31, 2081–2102. https://doi.org/10.1007/s11053-021-09982-7

（18）Wang C., Ma X., 2021,  Digital Geological Mapping. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_88-1

（17）Wang C., Ma X., 2021, Text Mining. In: Daya Sagar B., Cheng Q., McKinley J., Agterberg F. (eds) Encyclopedia of Mathematical Geosciences. Encyclopedia of Earth Sciences Series. Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_325-1

（16）Wang, C.*; Wang, X.; Chen, J., 2021. Digital Geological Mapping to Facilitate Field Data Collection, Integration, and Map Production in Zhoukoudian, China. Applied Sciences. 11, 5041. https://doi.org/10.3390/app11115041

（15）Ma, X., Ma, C., and Wang, C., 2020. A new structure for representing and tracking version information in a deep time knowledge graph.Computer and Geosciences, DOI:10.1016/j.cageo.2020.104620 【PDF】

（14）郑迎凯， 陈建国， 王成彬， 程潭武，2020.确定性系数与随机森林模型在云南芒市滑坡易发性评价中的应用.地质科技通报, 39(6):131-144

（13）Wang, C.*, Pan, Y., Chen, J.*, et al., 2020. Indicator Element Selection and Geochemical Anomaly Mapping Using Recursive Feature Elimination and Random Forest Methods in the Jingdezhen Region of Jiangxi Province, South China, Applied Geochemistry, 122,104760. DOI:10.1016/j.apgeochem.2020.104760【PDF】

（12）Wang, C. and Ma, X., 2019.Text Mining to Facilitate Domain Knowledge Discovery. In: Abdelkrim El Mouatasim (ed.), Text Mining - Analysis, Programming and Application. DOI：10.5772/intechopen.85362【PDF】

（11）Wang, C., Ma, X.*, Chen, J., 2018. Ontology-Driven Data Integration and Visualization for Exploring Regional Geologic Time and Paleontological Information, Computer & Geosciences. 115:12-19 DOI: 10.1016/j.cageo.2018.03.004 【PDF】

（10）Wang C., Chen J., 2019. Identification of concealed geological structures in a Grassland Area in Inner Mongolia, China: A Perspective from Temperature Vegetation Dryness Index (TVDI). Journal of Earth Science. 30(4): 853-860. DOI: 10.1007/s12583-017-0980-9  【PDF】

 （9）Wang, C., Ma, X., Chen, J. and, Chen J., 2018. Information Extraction and Knowledge Graph Construction from Geoscience Literature, Computer & Geosciences.112：112-120 DOI: 10.1016/j.cageo.2017.12.007 【PDF】【Most Cited Computers & Geosciences Articles】

（8）王成彬，马小刚，陈建国. 2018. 数据预处理在地学大数据中应用, 岩石学报.34(02):303-313【PDF】

（7）Ma X., Hummer D., Golden J., Fox P., Hazen R., Shaunna M., Downs R., Madhikarmi B., Wang C., Mayer M., 2017. Using visualized exploratory data analysis to facilitate collaboration and hypothesis generation in cross-disciplinary research, ISPRS International Journal of Geo-Information 6(11): 368-378【PDF】

 （6）Wang C., Chen J., Xiao F., Tounkara F. and Li L.,2016. Radioelement distributions and analysis of microtopographical influences in a shallow covered area, Inner Mongolia, China: Implications for mineral exploration, Journal of Applied Geophysics.133:62-69 DOI: 10.1016/j.jappgeo.2016. 06.013【PDF】

（5）Wang C., Rao J., Chen J., Ouyang Y., Qi S. and Li Q., 2016. Prospectivity Mapping for “Zhuxi type” Hydrothermal Cu-W Polymetallic Deposits in the Jingdezhen Region of Jiangxi Province, South China, Ore Geology Reviews.89:1-14 DOI: 10.1016/j.oregeorev.2017.05.022 【PDF】

（4）Wang C., 2014. Application of Empirical Model Decomposition and Independent Component Analysis to Magnetic Anomalies Separation: a case study for Gobi Desert coverage in Eastern Tianshan, China. The 16th annual conference of the International Association for Mathematical Geoscience. German: Springer 593-598 【PDF】

（3）Xiao F., Chen J., Agterberg F., Wang C., 2014. Element behavior analysis and its implications for geochemical anomaly identification: A case study for porphyry Cu–Mo deposits in Eastern Tianshan, China. Journal of Geochemical Exploration, 145: 1-11 【PDF】

（2）王成彬,陈建国,肖凡,吴光明,张珍玉. 2013.浙西北银山银多金属矿床地质特征及成因.地质与勘探,49(4):634-646【PDF】

（1）Xiao, F., Chen, J., Zhang, J., Wang, C., Wu, G., Agterberg, FP. 2012.Singularity mapping and spatially weighted principal component analysis to identify geochemical anomalies associated with Ag and Pb-Zn polymetallic mineralization in Northwest Zhejiang, China. Journal of Geochemical Exploration,122:90-100 【PDF】